Making the Rules: The Governance of Standard Development Organizations and their Policies on Intellectual Property Rights
Bibliographic record
Abstract
This study provides a comprehensive analysis of the governance of standard development organizations (SDOs), with a particular emphasis on organizations developing standards for Information and Communication Technologies (ICT). The analysis is based on 17 SDO case studies, a survey of SDO stakeholders, an expert workshop, and a comprehensive review of the legal and economic literature. The study considers the external factors conditioning SDO decision making on rules and procedures, including binding legal requirements, government influence, the network of cooperative relationships with other SDOs and related organizations, and competitive forces. SDO decision-making is also shaped by internal factors, such as the SDOs’ institutional architecture of decision-making bodies and their respective decision-making processes, which govern the interaction among SDO stakeholders and between stakeholders and the SDO itself. The study also analyzes governance principles, such as openness, balance of interests, and consensus decision-making, and discusses their interplay. The insights from these analyses are applied to SDO decision making on Intellectual Property Rights (IPR) policies, which represents a particularly salient and controversial aspect of SDO policy development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".